UAV Technology as an Effective Tool to Assess Chimpanzee Abundance in Degraded Landscapes

Estimating population size and density of a population of a species are essential to inform conservation management strategies and land-use planning. However, some landscapes dominated by fallow areas pose great challenges when it comes to traditional transect surveys. Unmanned aerial vehicle (UAV) and camera trapping technologies have demonstrated great potential when it comes to surveying wildlife. In this study, we employed camera trapping in combination with spatially explicit capture-recapture (SECR) models for estimating chimpanzee (Pan troglodytes verus) numbers in a non-protected area in the Moyamba district in south-western Sierra Leone, ca. 90 square kilometres. We estimated trapping rate per 1.25 km square grids across the target area based on a systematic layout of camera traps (N=30). In this environment practically devoid of forest, chimpanzees only nest in semi-domesticated oil palms (Elaeis guineensis) which are prevalent in the landscape. Due to the nesting specificity of the chimpanzees in this area, we were readily able to estimate nest density per grid and across the entire target area using drone imagery based on a sampling regime of 3 missions (200 meter square each) within each sample grid. We compared these abundance estimates with those generated from the SERC model and individual chimpanzee identification. Our study reveals that drone imagery data yields equivalent results and can effectively estimate chimpanzee population parameters across such degraded landscapes. The application of UAV technology in such environments can serve to inform conservation and land-use planning for chimpanzees, especially in areas prone to infrastructure and industrialized agricultural development.